Abstract:

An adaptive pulse compression method based on minimal mean square error (MMSE) estimation is presented to eliminate the conflict between the auto-correlation and cross-correlation of waveforms for fully polarimetric radars. The core concept of this method is to estimate the adaptive filter for a given range cell in a Bayesian sense through combining the echoes of corresponding polarization channel and employing the initial filter estimates of the surrounding range cells as a priori knowledge. This method can jointly separate received return signals from other polarization channels and implements pulse compression concurrently. The performances of this proposed method, including the mean-square error of the polarization scattering matrix and the detection probability, are analyzed over several stressing simulation scenarios. Simulation results show that the proposed method can effectively eliminate the interferences from adjacent range cells and different polarization channels, and is superior to standard matched filter for the pulse compression of fully polarimetric radars.